MIMO decoding in the presence of various interfering sources

ABSTRACT

A method of decoding a signal transmitted via a multiple input multiple output (MIMO) communication channel includes obtaining a first set of parameters associated with a first plurality of transmitters transmitting a plurality of intended streams, obtaining a second set of parameters associated with an interference source, receiving a plurality of streams including the plurality of intended streams; and decoding the plurality of intended streams using the first set of parameters and the second set of parameters.

CROSS REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional Patent App. No.60/971,324 entitled “MIMO Decoding in the Presence of VariousInterfering Sources,” filed Sep. 11, 2007, the disclosure of which ishereby expressly incorporated herein by reference.

FIELD OF TECHNOLOGY

The present disclosure relates generally toMultiple-Input-Multiple-Output (MIMO) Systems and, more particularly, todecoding signals in a MIMO system in the presence of interferingsources.

BACKGROUND

An ever-increasing number of relatively inexpensive, low power wirelessdata communication services, networks and devices have been madeavailable over the past number of years, promising near wire speedtransmission and reliability. Various wireless technology is describedin detail in the 802 IEEE Standards, including for example, the IEEEStandard 802.11a (1999) and its updates and amendments, the IEEEStandard 802.11g (2003), and the IEEE Standard 802.11n now in theprocess of being adopted, all of which are collectively incorporatedherein fully by reference. These standards have been or are in theprocess of being commercialized with the promise of 54 Mbps or higherdata rate, making them a strong competitor to traditional wired Ethernetand the more common “802.11b” or “WiFi” 11 Mbps mobile wirelesstransmission standard.

Generally speaking, transmission systems compliant with the IEEE 802.11aand 802.11g or “802.11a/g” as well as the 802.11n standards achievetheir high data transmission rates using Orthogonal Frequency DivisionMultiplexing (OFDM) encoded symbols mapped up to a 64 quadratureamplitude modulation (QAM) multi-carrier constellation. Generallyspeaking, the use of OFDM divides the overall system bandwidth into anumber of frequency sub-bands or channels, with each frequency sub-bandbeing associated with a respective sub-carrier upon which data may bemodulated. Thus, each frequency sub-band of the OFDM system may beviewed as an independent transmission channel within which to send data,thereby increasing the overall throughput or transmission rate of thecommunication system.

Generally, transmitters used in the wireless communication systems thatare compliant with the aforementioned 802.11a/802.11g/802.11n standardsas well as other standards such as the 802.16 IEEE Standard, performmulti-carrier OFDM symbol encoding (which may include error correctionencoding and interleaving), convert the encoded symbols into the timedomain using Inverse Fast Fourier Transform (IFFT) techniques, andperform digital to analog conversion and conventional radio frequency(RF) upconversion on the signals. These transmitters then transmit themodulated and upconverted signals after appropriate power amplificationto one or more receivers, resulting in a relatively high-speed timedomain signal with a large peak-to-average ratio (PAR).

Likewise, the receivers used in the wireless communication systems thatare compliant with the aforementioned 802.11a/802.11g/802.11n and 802.16IEEE standards generally include an RF receiving unit that performs RFdownconversion and filtering of the received signals (which may beperformed in one or more stages), and a baseband processor unit thatprocesses the OFDM encoded symbols bearing the data of interest.Generally, the digital form of each OFDM symbol presented in thefrequency domain is recovered after baseband downconversion,conventional analog to digital conversion and Fast FourierTransformation of the received time domain analog signal. Thereafter,the baseband processor performs frequency domain equalization (FEQ) anddemodulation to recover the transmitted symbols, and these symbols arethen processed in a viterbi decoder to estimate or determine the mostlikely identity of the transmitted symbol. The recovered and recognizedstream of symbols is then decoded, which may include deinterleaving anderror correction using any of a number of known error correctiontechniques, to produce a set of recovered signals corresponding to theoriginal signals transmitted by the transmitter.

In wireless communication systems, the RF modulated signals generated bythe transmitter may reach a particular receiver via a number ofdifferent propagation paths, the characteristics of which typicallychange over time due to the phenomena of multi-path and fading.Moreover, the characteristics of a propagation channel differ or varybased on the frequency of propagation. To compensate for the timevarying, frequency selective nature of the propagation effects, andgenerally to enhance effective encoding and modulation in a wirelesscommunication system, each receiver of the wireless communication systemmay periodically develop or collect channel state information (CSI) foreach of the frequency channels, such as the channels associated witheach of the OFDM sub-bands discussed above. Generally speaking, CSI isinformation defining or describing one or more characteristics abouteach of the OFDM channels (for example, the gain, the phase and the SNRof each channel). Upon determining the CSI for one or more channels, thereceiver may send this CSI back to the transmitter, which may use theCSI for each channel to precondition the signals transmitted using thatchannel so as to compensate for the varying propagation effects of eachof the channels.

To further increase the number of signals which may be propagated in thecommunication system and/or to compensate for deleterious effectsassociated with the various propagation paths, and to thereby improvetransmission performance, it is known to use multiple transmit andreceive antennas within a wireless transmission system. Such a system iscommonly referred to as a multiple-input, multiple-output (MIMO)wireless transmission system and is specifically provided for within the802.11n IEEE Standard now being adopted. Further, the 802.16 standard,or WiMAX, applies to cell-based systems and supports MIMO techniques.Generally speaking, the use of MIMO technology produces significantincreases in spectral efficiency and link reliability of 802.xx andother systems, and these benefits generally increase as the number oftransmission and receive antennas within the MIMO system increases.

In addition to the frequency channels created by the use of OFDM, a MIMOchannel formed by the various transmit and receive antennas between aparticular transmitter and a particular receiver includes a number ofindependent spatial channels. As is known, a wireless MIMO communicationsystem can provide improved performance (e.g., increased transmissioncapacity) by utilizing the additional dimensionalities created by thesespatial channels for the transmission of additional data. Of course, thespatial channels of a wideband MIMO system may experience differentchannel conditions (e.g., different fading and multi-path effects)across the overall system bandwidth and may therefore achieve differentSNRs at different frequencies (i.e., at the different OFDM frequencysub-bands) of the overall system bandwidth. Consequently, the number ofinformation bits per modulation symbol (i.e., the data rate) that may betransmitted using the different frequency sub-bands of each spatialchannel for a particular level of performance may differ from frequencysub-band to frequency sub-band.

However, instead of using the various different transmission and receiveantennas to form separate spatial channels on which additionalinformation is sent, better transmission and reception properties can beobtained in a MIMO system by using each of the various transmissionantennas of the MIMO system to transmit the same signal while phasing(and amplifying) this signal as it is provided to the varioustransmission antennas to achieve beamforming or beamsteering. Generallyspeaking, beamforming or beamsteering creates a spatial gain patternhaving one or more high gain lobes or beams (as compared to the gainobtained by an omni-directional antenna) in one or more particulardirections, while reducing the gain over that obtained by anomni-directional antenna in other directions. If the gain pattern isconfigured to produce a high gain lobe in the direction of each of thereceiver antennas, the MIMO system can obtain better transmissionreliability between a particular transmitter and a particular receiver,over that obtained by single transmitter-antenna/receiver-antennasystems.

The transmitters and receivers in the wireless communication system mayeach be capable of using a variety of modulation schemes. For example,some modulations schemes may provide a higher bit rate than otherschemes (e.g., 64-QAM vs. 16-QAM). Typically, modulation schemes thatprovide a higher bit rate may be more sensitive to channel impairmentsas compared to modulation schemes with a lower bit rate.

Thus, certain modern wireless communications occur over a number ofchannels in which multiple transmitters simultaneously transmit tomultiple receivers. As is known, several factors affect the spectralefficiency of a wireless communication system, i.e., the ability of thesystem to optimally use the band of available frequencies. In oneaspect, inter-symbol interference (ISI) arises when a signal from atransmitting antenna is reflected off various obstacles, therebycreating a multi-path propagation channel between the transmittingantenna and the intended receiver. Because multiple copies of atransmitted symbol may arrive at the receiving antenna with differentpropagation delays, the received signal may have blurry boundariesbetween sequentially transmitted symbols.

In another aspect, systems such as WiMAX include base stations definingareas of coverage, or cells, in which users (e.g., mobile stations,portable or stationary devices, etc.) communicate through the cellularnetwork including the base stations. More specifically, base stationshave one or several antennas to which users transmit “uplink” data andfrom which users receive “downlink” data. In these systems, proximatetransmitters operating on the same carrier frequency createinter-channel interference (ICI), further reducing the quality andreliability of reception. As a result, cellular-type wireless systems ingeneral, and those that utilize MIMO modulation in particular, typicallydo not use the same frequency in adjacent cells. For example, asillustrated in FIG. 1, a wireless system 10 in which the equally sizedcells 12 cover the entire geographic area, has a frequency reuse of ⅓because each of the frequencies 20-26 can be used in at most ⅓ of totalnumber of cells 12. As a result, the efficiency of the wireless system10 is significantly limited.

SUMMARY

In one embodiment, a method of decoding a signal transmitted via amultiple input multiple output (MIMO) communication channel includesobtaining a first set of parameters associated with a first plurality oftransmitters transmitting a plurality of intended streams, obtaining asecond set of parameters associated with an interference source,receiving a plurality of streams including the plurality of intendedstreams, and decoding the plurality of intended streams using the firstset of parameters and on the second set of parameters.

In another embodiment, a smart receiver for decoding a signaltransmitted via a multiple input multiple output (MIMO) communicationchannel includes a plurality of antennas which receive a plurality ofstreams including a set of intended streams and a set of interferencestreams via the MIMO channel, a demodulator that demodulates theplurality of streams based on at least first channel data associatedwith the set of intended streams and second channel data associated withthe set of interference streams, a deinterleaver that receives thedemodulated plurality of streams and restores a sequence of symbols, anda decoder that decodes the restored sequence of symbols.

In another embodiment, a method of decoding, at a first wireless device,a signal including a plurality of streams from a second wireless devicecommunicating in a MIMO mode with the first wireless device includesreceiving a first channel description associated with a first cell inwhich the first wireless device and the second wireless device operate,receiving a second channel description associated with a second cell,constructing a channel model using the first channel description and onthe second channel description, receiving the signal, and decoding thesignal according to the constructed channel model.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 schematically illustrates a cellular wireless system having afrequency reuse of ⅓;

FIG. 2 is a block diagram illustrating co-channel interference in a MIMOsystem;

FIG. 3 is a block diagram of a receiver capable of MIMO decoding in thepresence of various interference sources;

FIG. 4 is an exemplary flowchart of an algorithm for decodingnon-space-time-coded signals using equalization, implemented by areceiver consistent with FIG. 3;

FIG. 5 is an exemplary flowchart of an algorithm for decodingnon-space-time-coded signals with no equalization, implemented by areceiver consistent with FIG. 3;

FIG. 6 is an exemplary flowchart of an algorithm for decodingAlamouti-coded intended signals, implemented by a receiver consistentwith FIG. 3;

FIG. 7 is an exemplary flowchart of an algorithm for decoding signals inthe presence of Alamouti-coded interfering signals, implemented by areceiver consistent with FIG. 3;

FIG. 8 is an exemplary flowchart of an algorithm for decodingAlamouti-coded intended signals in the presence of Alamouti-codedintended and interfering signals, implemented by a receiver consistentwith FIG. 3;

FIG. 9A is a block diagram of a high definition television that mayutilize a method and system for decoding MIMO signals in the presence ofvarious interference sources such as described herein;

FIG. 9B is a block diagram of a vehicle that may utilize a method andsystem for decoding MIMO signals in the presence of various interferencesources such as described herein;

FIG. 9C is a block diagram of a cell phone that may utilize a method andsystem for decoding MIMO signals in the presence of various interferencesources such as described herein;

FIG. 9D is a block diagram of a set top box that may utilize a methodand system for decoding MIMO signals in the presence of variousinterference sources such as described herein;

FIG. 9E is a block diagram of a media player that may utilize a methodand system for decoding MIMO signals in the presence of variousinterference sources such as described herein; and

FIG. 9F is a block diagram of a voice-over-IP (VoIP) player that mayutilize a method and system for decoding MIMO signals in the presence ofvarious interference sources such as described herein.

DETAILED DESCRIPTION

FIG. 2 is a block diagram illustrating an example MIMO wirelesscommunication system 200 in which multiple transmitters, such as adevice 202 and a device 204, simultaneously transmit over a sharedwireless communication channel 206. Each of the devices 202 and 204 maybe a base station or a mobile station equipped with a set of antennas210-218 and 220-228, respectively. Of course, the wireless communicationsystem 200 may include any number of devices, each equipped with thesame or a different number of antennas. The number of antennas of eachdevice may be any suitable number such as 1, 2, 3, 4, . . . . Thus, somedevices may be equipped with only a single antenna.

In one operational state, the antennas 210-218 may operate astransmitters to transmit several intended streams of information 230 toone or more antennas 250. More specifically, the antennas 210-218 mayoperate in any of the MIMO modes or schemes, including those known inthe art. For example, the device 202 may use the antennas 210-218 toimprove channel diversity by transmitting multiple copies of the samesymbol via several streams. Alternatively, the device 202 may transmitdifferent symbols via each of the antennas 210-218 to increasethroughput. As yet another alternative, the device 202 may operate in amixed MIMO mode to improve both channel diversity and throughput.

In another operational state, the antennas 210-218 may operate asreceivers and may listen to incoming traffic from the one or moreantennas 250. Thus, in this state, the antennas 210-218 may be receiversand the antennas 250 may be transmitters. It will be noted, however,that the antennas 210-218 or 220-228 need not operate in multiple (e.g.,receive, transmit, etc.) states in at least some of the applications. Inapplication to high-definition television, for example, the antennas210-218 may operate solely as receivers. On the other hand, if thedevice 202 is a mobile station in a WiMAX communication network, theantennas 210-218 may support both uplink and downlink transmissions.Additionally, there may be separate transmit antennas and separatereceive antennas.

In addition to the intended streams 230 from the antennas 210-218, theantennas 250 operating in a receive mode may pick up interferencestreams 260 directed from the antennas 220-228 to the antennas 262 ifthe streams 230 and 260 share the carrier frequency or a band of carrierfrequencies. Similarly, the antennas 262 may pick up the streams 230from the antennas 250 as interference (with respect to the streams 260intended for the antennas 262). As discussed above with reference toFIG. 1, the devices 202 and 204 operating in the existing communicationsystems do not transmit at the same frequency at the same time unlessthe devices 202 and 204 are sufficiently far apart for the amplitudes ofthe mutually interfering streams 230 and 260 to have substantially fadedat the respective non-intended receivers, i.e., the antennas 250 and262. If, for the example, the devices 202 and 204 are base stationsdefining respective cells in a WiMAX network, these cells typicallycannot be adjacent to each other and, accordingly, the frequency reuseis not equal to one. As an equally undesirable alternative, the devices202 and 204 may operate in the same frequency band in the adjacent orproximate cells but the throughput to the respective receivers may berelatively low due to the resulting high inter-channel interference.

It will be further noted that the antennas 210-218, for example, maydefine different numbers of streams 230 in various embodiments orconfigurations of the device 202. Typically, the number of spatialstreams associated with a shared communication channel (such as thechannel 206) is less than or equal to the number of transmit antennas.Further, each stream may correspond to a separate encoder chain (e.g.,an encoder, an interleaver, a modulator) or, alternatively, a sharedencoder chain may operate on multiple streams. For example, the device202 in FIG. 2 includes an encoder, an interleaver, and a modulatorservicing several streams 230, whereas the device 204 includes twoencoder chains, each directing one or several respective streams to ashared symbol-to-stream mapper. WiMAX standards, to take anotherexample, currently support both a single-encoder option and atwo-encoder option for a two-transmit-antenna configuration. In general,the number of encoders and/or encoder chains may be less than or equalto the number of transmitted streams.

Thus, as illustrated in FIG. 2, the wireless communication channel 206may include the intended channel defined by the intended streams 230, aninterfering channel defined by the interfering streams 260 and, in somecases, one or several additional interfering channels, each having oneor more interfering streams. For the purposes of convenience, the term“channel” is used herein to refer to the combined channel including boththe intended and at least the highly relevant interfering sources. Moreprecisely, the mathematical models discussed below use the term“channel” to refer to a set of parameters defining such combinedchannel.

Referring to FIG. 3, a receiver 300 equipped with antennas 302-308 mayreceive and properly decode information from one or more intendedtransmitters operating in a shared wireless communication channel in thepresence of various interfering sources such as, for example,interfering transmitters operating in the same carrier frequency band inan adjacent cell, or otherwise in close proximity to the intendedtransmitters. Receivers such as the receiver 300 may be referred to as“smart receivers.” Because the smart receiver 300 can estimate thechannel associated with the interfering transmitters and separate theinterference streams from the intended streams, the smart receiver 300does not require that other transmitters using the same frequency bandoperate in non-adjacent cells to maintain high throughput. Thearchitecture and operation of the smart receiver 300 is discussed belowwith reference to FIG. 3, and the application of the smart receiver 300to some of the known MIMO modes is further discussed with reference toFIG. 3 and to the example flow diagrams illustrated in FIGS. 4-8.

In operation, the smart receiver 300 may obtain information regardingthe one or more interfering channels in a wired or wireless manner. Forexample, the smart receiver 300 may be a base station (or a module in abase station) communicatively coupled to a base station 322 and to abase station 324 via a wired network backbone 330. The base stations300, 322 and 324 may each support multiple mobile stationscommunicating, for example, according to an OFDMA scheme configuredoptionally to use the same frequency band. By using any suitable networkprotocol, the base stations 300, 322, and 324 may exchange suchinformation as modulation schemes, MIMO mode, etc. and, based on thereceived information, estimate a set of parameters to generate a channelmodel discussed in more detail below. To continue with this example, themobile stations operating in the cells supported by the base stations322 and 324 may be significant sources of interference for the basestation 300 during receiving and decoding of the intended streams fromone or more mobile stations operating in the cell supported by the basestation 300. Of course, if the base stations 300, 322, and 324 do notswitch between the transmit and receive modes in a synchronized manner,the signals from the base stations 322 and 324 may create additionalinterference for the base station 300.

Additionally or alternatively, the smart receiver 300 may estimatechannel information due to the interfering mobile stations in theadjacent cell by processing substantially unique pseudo-noise (PN)sequences from the neighbor base stations or from the mobile stationscommunicating with these base stations. As yet another alternative, thebase station equipped with the smart receiver 300 may store at leastsome of the information necessary for estimating the interfering channelas part of base station configuration data. Thus, based on theinformation received via the wired backbone, the wireless network, orboth, the smart receiver 300 operating as a base station may estimatethe uplink channel as a set of both the intended streams and theinterfering streams.

On the other hand, the smart receiver 300 operating as a mobile station(or as a module in a mobile station) may estimate the downlink channel,including both the parameters related to the intended streams and to theinterfering streams, based on wireless signals only. As one example, amobile station operating in a WiMAX network may estimate the portion ofthe channel related to the interfering sources from a Downlink Map(DL-MAP) message broadcast by the adjacent base stations using the samecarrier frequency as the frequency on which the mobile station receivesthe one or more intended streams. As is known, the DL-MAP messagespecifies the allocation of resources (i.e., carrier frequencies,timeslots, etc.) in the OFDMA scheme. Thus, by processing DL-MAPmessages from one or several adjacent base stations in addition to thebase station with which the mobile station is currently communicating,the mobile station can obtain a set of parameters that may be used forconstructing the channel model discussed below. Further, a mobilestation may obtain these or additional channel parameters from theperiodic broadcasts of PN sequences, similarly to processing of PNsequences at a base station discussed above.

Upon collecting the information necessary for quantifying the effect ofco-channel interference, the smart receiver 300 operating in a basestation or in a mobile station may separate the intended streams fromthe interfering streams by utilizing a model such as:y=Hx+z, where

${y = {{\begin{bmatrix}y_{1} \\y_{2} \\\vdots \\y_{N_{R}}\end{bmatrix}\mspace{14mu} H} = {{\begin{bmatrix}h_{1,1} & h_{1,2} & \cdots & h_{1,N_{TS}} \\h_{2,1} & h_{2,2} & \cdots & h_{2,N_{TS}} \\\vdots & \vdots & \vdots & \vdots \\h_{N_{R},1} & h_{N_{R},2} & \cdots & h_{N_{R},N_{TS}}\end{bmatrix}\mspace{14mu} x} = \begin{bmatrix}x_{1} \\x_{2} \\\vdots \\x_{N_{TS}}\end{bmatrix}}}}\;$ ${z = \begin{bmatrix}z_{1} \\z_{2} \\\vdots \\z_{N_{R}}\end{bmatrix}},$in which y represents, in vector from, the receive signal, H representsthe MIMO communication channel, x represents the transmit signal, and zrepresents the noise vector. More precisely, y_(r) is a receive signalat antenna r and z_(r) is noise at an antenna r. Accordingly, the numberof receive antennas included in the model illustrated above is N_(R).Meanwhile, according to this model, a transmit stream x_(s) is anintended stream if 1≦s≦N_(S) or an interference stream ifN_(S+1)≦s≦N_(TS). Thus, the model accounts for the total of N_(TS)streams in the MIMO channel. Of course, the model may be applied to asingle interference source in the transmit signal vector x or severalinterference sources such as multiple adjacent base stations eachequipped with several antennas, for example.

The MIMO communication channel H includes channel gain parametersh_(r,s) representing channel gain in a stream s at a receive antenna r.In at least some of the embodiments, each channel gain h_(r,s) is acomplex number that incorporates an amplitude factor and a phase shiftfactor. In other words, each h_(r,s) parameter may represent anattenuation coefficient associated with a certain propagation path asused in, for example, a Rayleigh fading channel model. In general, themodel y=Hx+z may represent any MIMO mode such as space-time encoding,spatial multiplexing, beam forming, etc. The smart receiver 300 mayestimate the parameters h_(r,s) by collecting information from theadjacent transmitters/receivers in a wired and/or wireless manner, asdiscussed above.

With continued reference to FIG. 3, the smart receiver 300 may decodethe received signals in accordance with the model discussed above. Inparticular, in order to separate the intended signals from theinterference signals, the receiver 300 may pre-process the signals fromthe antennas 302-308 in a pre-processor for space-time code 310,optionally equalize the received signals in a MIMO equalizer 312,demodulate the received signals in a demodulator 314, process thedemodulated signals in a deinterleaver 316 if necessary, and finallydecode the signals in a decoder 318 to generate information symbols 320.Depending on the amount of noise and on quality of the MIMO channel, thefully decoded information bits 320 may arrive at a high data rate with alow error rate.

The components or modules 310-318 may be implemented as hardware,software, firmware, or mixed components. For example, some or all of thecomponents may be custom integrated circuits, application-specificintegration circuits (ASICs), etc., communicatively coupled byelectrical busses. In this case, the smart receiver 300 optionally mayinclude bypass busses (not shown) to bypass some of the components ifthe currently active MIMO mode does not require certain operations, suchas processing multiple presentations of a symbol encoded according to aspace-time encoding scheme. Alternatively, some or all of the modules310-318 may be software modules, stored in a computer-readable memoryand executed on a processor. Other implementations of the modules310-318 are also possible such as using a combination of hardware,software, and/or firmware.

As indicated above, the smart receiver 300 in some embodiments or insome modes of operation may not use include one or more of the modules310-318 or, alternatively, may not use each of the modules 310-318 indecoding the received signals. For example, the smart receiver 300 maynot use the pre-processor for space-time code 310 if neither theintended streams nor the interfering streams are space-time encoded. Insome embodiments, the smart receiver 300 may quickly switch betweenseveral modes of decoding (e.g., spatial multiplexing to beamforming) inresponse to changes in network conditions, such as due to the smartreceiver 300 moving into a different geographical area in which usersrely on a different MIMO mode. Thus, the data received by the antennas302-308 may bypass at least some of the modules 310-318 depending on theMIMO mode, user preferences, computational cost, etc. Further, it willbe appreciated that some of the modules 310-318 may be combined or,conversely, divided into smaller components.

As one example particularly relevant to decoding ofnon-space-time-encoded signals, the smart receiver 300 may direct datareceived by the antennas 302-308 to the MIMO equalization module 312. Ingeneral, the MIMO equalization module 312 may implement any suitableMIMO equalization techniques, including those known in the art. Forexample, the MIMO equalization module 312 may operate as a zero-forcing(ZF) linear equalizer (LE), a minimum mean square error liner equalizer(MMSE LE), a ZF decision feedback equalizer (DFE), an MMSE DFE, etc. Asa more specific example, the MIMO equalization module 312 may apply theZF approach to a channel in which the number of receive antennas (N_(r))is two, the number of intended streams (N_(S)) is two, and the totalnumber of streams (N_(TS)) is four. Accordingly, rather than operatingwith the original modely=Hx+z,

$\begin{bmatrix}y_{1} \\y_{2}\end{bmatrix} = {{\begin{bmatrix}h_{1,1} & h_{1,2} & h_{1,3} & h_{1,4} \\h_{2,1} & h_{2,2} & h_{2,3} & h_{2,4}\end{bmatrix}\begin{bmatrix}x_{1} \\x_{2} \\x_{3} \\x_{4}\end{bmatrix}} + \begin{bmatrix}z_{1} \\z_{2}\end{bmatrix}}$the smart receiver 300 may work with an equalized model{tilde over (y)}={tilde over (H)}x+{tilde over (z)}

$\begin{bmatrix}{\overset{\sim}{y}}_{1} \\{\overset{\sim}{y}}_{2}\end{bmatrix} = {{\begin{bmatrix}1 & 0 & {\overset{\sim}{h}}_{1,3} & {\overset{\sim}{h}}_{1,4} \\0 & 1 & {\overset{\sim}{h}}_{2,3} & {\overset{\sim}{h}}_{2,4}\end{bmatrix}\begin{bmatrix}x_{1} \\x_{2} \\x_{3} \\x_{4}\end{bmatrix}} + {\begin{bmatrix}{\overset{\sim}{z}}_{1} \\{\overset{\sim}{z}}_{2}\end{bmatrix}.}}$It is apparent that the equalized channel matrix {tilde over (H)} forcesx₂ and x₁ to zero when calculating {tilde over (y)}₁ and {tilde over(y)}₂, respectively, thereby canceling the mutual impact of the intendedstreams.

To continue with this example, the demodulator 314 may next estimateeach received symbol by using the log-likelihood ratio (LLR) approach.As is known, the LLR approach is a statistical algorithm which, whenapplied to signal transmissions, yields a probable value of atransmitted symbol from a known dictionary of symbols. In this sense,the probable values of the transmitted symbols may be understood as softinformation. In operation, the demodulator 314 may calculate the LLRvalue for the i-th symbol in the first intended stream x₁ by applyingthe formula

${{LLR}_{1,I} = {{\log\left( {\sum\limits_{{x\varepsilon X}_{1,I}^{(1)}}\;{\exp\left( \frac{{{{\overset{\sim}{y}}_{1} - {{\overset{\sim}{h}}_{{row},1}x}}}^{2}}{\sigma_{{\overset{\sim}{z}}_{1}}^{2}} \right)}} \right)} - {\log\left( {\sum\limits_{{x\varepsilon X}_{1,I}^{(0)}}\;{\exp\left( \frac{{{{\overset{\sim}{y}}_{1} - {{\overset{\sim}{h}}_{{row},1}x}}}^{2}}{\sigma_{{\overset{\sim}{z}}_{1}}^{2}} \right)}} \right)}}},$where it {tilde over (h)}_(row,r) is r-th row of {tilde over (H)} andX_(s,I) ^((b)) is a set of vectors of signal constellation points whosevalue in the I-th symbol position of the s-th element is equal to b, andwhere σ is variance of the noise.

In another embodiment or when operating in a different mode, the smartreceiver 300 may directly proceed to calculating LLR values in thedemodulator 314 without performing MIMO equalization in the module 310if the incoming data is non-space-time encoded. In other words, thesmart receiver 300 may not generate an equivalent model and may insteaduse the more computationally complicated model y=Hx+z to calculatemaximum-likelihood (ML) LLR values:

${LLR}_{s,l} = {{\log\left( {\sum\limits_{x\; \in X_{1,l}^{(1)}}{\exp\left( \frac{{{y - {Hx}}}^{2}}{\sigma_{z}^{2}} \right)}} \right)} - {{\log\left( {\sum\limits_{x\; \in X_{1,l}^{(0)}}{\exp\left( \frac{{{y - {Hx}}}^{2}}{\sigma_{z}^{2}} \right)}} \right)}.}}$

When calculating LLR values without a prior MIMO equalization, thedemodulator 314 or another component of the smart receiver 300 may alsosimplify the computation based on max-log-map approximation. As anotheralternative, the smart receiver 300 may reduce the complexity ofequalization-free LLR computation by decomposing the matrix H into anorthogonal and a triangular matrix (e.g., by performing the knowntechnique of QR decomposition). If a certain embodiment of the smartreceiver 300 relies on QR decomposition, the demodulator 314 may workwith Q*y and R rather than with y and H, where * denotes a complexconjugate.

As mentioned above, the intended streams, the interfering streams, orboth may also be space-time coded in a MIMO communication system. As isknown, space-time MIMO coding frequently relies on the so-calledAlamouti approach. To consider the simplest example of this technique, atransmitter may transmit in two timeslots using two antennas accordingto the coding matrix:

$C_{A} = {\begin{bmatrix}s_{1} & s_{2} \\{- s_{2}^{\star}} & s_{1}^{*}\end{bmatrix}.}$Thus, the transmitter may transmit symbols s₁ and s₂ during the firsttime slot followed by −s₂* and −s₁* the second time slot using the firstand the second antenna, respectively.

At the two receive antennas, the operation according to the codingmatrix C_(A) may be modeled as:

${\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 2\rbrack}\end{bmatrix} = {{\begin{bmatrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 1\rbrack} & {h_{2,2}\lbrack 1\rbrack}\end{bmatrix}\begin{bmatrix}x_{1} \\x_{2}\end{bmatrix}} + \begin{bmatrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack}\end{bmatrix}}},{\begin{bmatrix}{y_{1}\lbrack 2\rbrack} \\{y_{2}\lbrack 2\rbrack}\end{bmatrix} = {{\begin{bmatrix}{h_{1,1}\lbrack 2\rbrack} & {h_{1,2}\lbrack 2\rbrack} \\{h_{2,1}\lbrack 2\rbrack} & {h_{2,2}\lbrack 2\rbrack}\end{bmatrix}\begin{bmatrix}{- x_{2}^{\star}} \\x_{1}^{*}\end{bmatrix}} + \begin{bmatrix}{z_{1}\lbrack 2\rbrack} \\{z_{2}\lbrack 2\rbrack}\end{bmatrix}}},{{{and}\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 1\rbrack} \\{y_{1}^{*}\lbrack 2\rbrack} \\{y_{2}^{*}\lbrack 2\rbrack}\end{bmatrix}} = {{\begin{bmatrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 1\rbrack} & {h_{2,2}\lbrack 1\rbrack} \\{h_{1,2}^{*}\lbrack 2\rbrack} & {- {h_{1,1}^{*}\lbrack 2\rbrack}} \\{h_{2,2}^{*}\lbrack 2\rbrack} & {- {h_{2,1}^{*}\lbrack 2\rbrack}}\end{bmatrix}\begin{bmatrix}x_{1} \\x_{2}\end{bmatrix}} + \begin{bmatrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack} \\{z_{1}^{*}\lbrack 2\rbrack} \\{z_{2}^{*}\lbrack 2\rbrack}\end{bmatrix}}}$

With continued reference to FIG. 3, the smart receiver 300 may model theconfiguration in which the intended streams are Alamouti-coded but theinterfering signals are not Alamouti-coded as:

${{\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 2\rbrack}\end{bmatrix} =}\quad}{\quad{{{\left\lbrack {\begin{matrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 1\rbrack} & {h_{2,2}\lbrack 1\rbrack}\end{matrix}\begin{matrix}{h_{1,3}\lbrack 1\rbrack} \\{h_{2,3}\lbrack 1\rbrack}\end{matrix}\begin{matrix}{h_{1,4}\lbrack 1\rbrack} \\{h_{2,4}\lbrack 1\rbrack}\end{matrix}} \right\rbrack\begin{bmatrix}x_{1} \\x_{2} \\{x_{3}\lbrack 1\rbrack} \\{x_{4}\lbrack 1\rbrack}\end{bmatrix}} + {\begin{bmatrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack}\end{bmatrix}\mspace{14mu}{{and}\begin{bmatrix}{y_{1}\lbrack 2\rbrack} \\{y_{2}\lbrack 2\rbrack}\end{bmatrix}}}} = {{\left\lbrack {\begin{matrix}{h_{1,1}\lbrack 2\rbrack} & {h_{1,2}\lbrack 2\rbrack} \\{h_{2,1}\lbrack 2\rbrack} & {h_{2,2}\lbrack 2\rbrack}\end{matrix}\begin{matrix}{h_{1,3}\lbrack 2\rbrack} \\{h_{2,3}\lbrack 2\rbrack}\end{matrix}\begin{matrix}{h_{1,4}\lbrack 2\rbrack} \\{h_{2,4}\lbrack 2\rbrack}\end{matrix}} \right\rbrack\begin{bmatrix}{- x_{2}^{*}} \\x_{1}^{*} \\{x_{3}\lbrack 2\rbrack} \\{x_{4}\lbrack 2\rbrack}\end{bmatrix}} + \begin{bmatrix}{z_{1}\lbrack 2\rbrack} \\{z_{2}\lbrack 2\rbrack}\end{bmatrix}}}\mspace{14mu}}$in the case where N_(r)=2, N_(S)=2, and N_(TS)=4.

Thus, the pre-processor for space-time code 310 may perform Alamoutireceiver manipulation prior to propagating the received data to thecomponents 312-318. The smart receiver 300 may construct an equivalentreceive signal model as{tilde over (y)}={tilde over (H)}x+{tilde over (z)},

$\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 1\rbrack} \\{y_{1}^{*}\lbrack 2\rbrack} \\{y_{2}^{*}\lbrack 2\rbrack}\end{bmatrix} = {\left\lbrack \begin{matrix}h_{1,1} & \lbrack 1\rbrack & h_{1,2} & \lbrack 1\rbrack & h_{1,3} & \lbrack 1\rbrack & h_{1,4} & \lbrack 1\rbrack & 0 & 0 \\h_{2,1} & \lbrack 2\rbrack & h_{2,2} & \lbrack 2\rbrack & h_{2,3} & \lbrack 2\rbrack & h_{2,4} & \lbrack 2\rbrack & 0 & 0 \\h_{1,2}^{*} & \lbrack 2\rbrack & {- h_{1,1}^{*}} & \lbrack 2\rbrack & 0 & 0 & h_{1,3}^{*} & \lbrack 2\rbrack & h_{1,4}^{*} & \lbrack 2\rbrack \\h_{2,2}^{*} & \lbrack 2\rbrack & {- h_{2,1}^{*}} & \lbrack 2\rbrack & 0 & 0 & h_{2,3}^{*} & \lbrack 2\rbrack & h_{2,4}^{*} & \lbrack 2\rbrack\end{matrix} \right\rbrack{\quad{\left\lbrack \begin{matrix}x_{1} \\x_{2} \\{x_{3}\lbrack 1\rbrack} \\{x_{4}\lbrack 1\rbrack} \\{x_{3}^{*}\lbrack 2\rbrack} \\{x_{4}^{*}\lbrack 2\rbrack}\end{matrix} \right\rbrack + \begin{bmatrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack} \\{z_{1}^{*}\lbrack 2\rbrack} \\{z_{2}^{*}\lbrack 2\rbrack}\end{bmatrix}}}}$

Using the model illustrated above and applying the ML approach, thedemodulator 314 may calculate the LLR values for the bit I in the streams according to the formula:

${{LLR}_{s,I} = {{\log\left( {\sum\limits_{\overset{\sim}{x}\varepsilon{\overset{\sim}{X}}_{1,I}^{(1)}}\;{\exp\left( \frac{{{\overset{\sim}{y} - {\overset{\sim}{H}\overset{\sim}{x}}}}^{2}}{\sigma_{z}^{2}} \right)}} \right)} - {\log\left( {\sum\limits_{\overset{\sim}{x}\varepsilon{\overset{\sim}{X}}_{1,I}^{(0)}}\;{\exp\left( \frac{{{\overset{\sim}{y} - {\overset{\sim}{H}\overset{\sim}{x}}}}^{2}}{\sigma_{z}^{2}} \right)}} \right)}}},$where {tilde over (X)}_(s,I) ^((b)) is a set of vectors of signalconstellation points whose value in the I-th bit position of the s-thelement is equal to b, and where σ is variance of the noise. As in theexample of decoding non-space-time-coded signals discussed above, themax-log-approximation, or any other suitable approximation technique,may be used as well. It will be noted that optionally, the smartreceiver 300 may simplify the LLR computation by using the MIMOequalizer 312 after performing Alamouti receiver manipulation at themodule 310 but prior to processing the signals in the module 314.

If, on the other hand, the smart receiver 300 ascertains that theintended streams are not space-time coded but the interfering streamsare Alamouti-coded, the smart receiver may model the received signalsas:

${\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 1\rbrack}\end{bmatrix} = {{{\begin{bmatrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} & {h_{1,3}\lbrack 1\rbrack} & {h_{1,4}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 1\rbrack} & {h_{2,2}\lbrack 1\rbrack} & {h_{2,3}\lbrack 1\rbrack} & {h_{2,4}\lbrack 1\rbrack}\end{bmatrix}\begin{bmatrix}{x_{1}\lbrack 1\rbrack} \\{x_{2}\lbrack 1\rbrack} \\x_{3} \\x_{4}\end{bmatrix}} + {\begin{bmatrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack}\end{bmatrix}{\mspace{11mu}\;}{{and}\begin{bmatrix}{y_{1}\lbrack 2\rbrack} \\{y_{2}\lbrack 2\rbrack}\end{bmatrix}}}} = {{\begin{bmatrix}{h_{1,1}\lbrack 2\rbrack} & {h_{1,2}\lbrack 2\rbrack} & {h_{1,3}\lbrack 2\rbrack} & {h_{1,4}\lbrack 2\rbrack} \\{h_{2,1}\lbrack 2\rbrack} & {h_{2,2}\lbrack 2\rbrack} & {h_{2,3}\lbrack 2\rbrack} & {h_{2,4}\lbrack 2\rbrack}\end{bmatrix}\begin{bmatrix}{x_{1}\lbrack 2\rbrack} \\{x_{2}\lbrack 2\rbrack} \\{- x_{4}^{*}} \\{- x_{3}^{*}}\end{bmatrix}} + \begin{bmatrix}{z_{1}\lbrack 2\rbrack} \\{z_{2}\lbrack 2\rbrack}\end{bmatrix}}}}\mspace{11mu}$in a configuration where N_(r)=2, N_(S)=2, and N_(TS)=4. Based on thismodel, the smart receiver may decode the streams by constructing andapplying the equivalent model:{tilde over (y)}={tilde over (H)}x+{tilde over (z)}

$\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 1\rbrack} \\{y_{1}^{*}\lbrack 2\rbrack} \\{y_{2}^{*}\lbrack 2\rbrack}\end{bmatrix} = {{\begin{bmatrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} & 0 & 0 & {h_{1,3}\lbrack 1\rbrack} & {h_{1,3}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 2\rbrack} & {h_{2,2}\lbrack 2\rbrack} & 0 & 0 & {h_{2,3}\lbrack 2\rbrack} & {h_{2,4}\lbrack 2\rbrack} \\0 & 0 & {h_{1,1}^{*}\lbrack 2\rbrack} & {h_{1,2}^{*}\lbrack 2\rbrack} & {h_{1,4}^{*}\lbrack 2\rbrack} & {- \;{h_{1,3}^{*}\lbrack 2\rbrack}} \\0 & 0 & {h_{2,1}^{*}\lbrack 2\rbrack} & {h_{2,2}^{*}\lbrack 2\rbrack} & {h_{2,4}^{*}\lbrack 2\rbrack} & {- \;{h_{2,3}^{*}\lbrack 2\rbrack}}\end{bmatrix}\left\lbrack \begin{matrix}{x_{1}\lbrack 1\rbrack} \\{x_{2}\lbrack 1\rbrack} \\{x_{1}^{*}\lbrack 2\rbrack} \\{x_{2}^{*}\lbrack 2\rbrack} \\x_{3} \\x_{4}\end{matrix} \right\rbrack} + \begin{bmatrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack} \\{z_{1}^{*}\lbrack 2\rbrack} \\{z_{2}^{*}\lbrack 2\rbrack}\end{bmatrix}}$and calculating LLR values in a manner similar to the case discussedabove with reference to Alamouti-encoded intended streams in thepresence of interfering non-Alamouti-encoded streams.

Further, it is possible for both the intended streams and for theinterfering streams to be space-time coded and, in particular, to becoded according to the Alamouti algorithm. In this case, the signalsarriving at the receive antennas 302-308 may be modeled as:

$\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 1\rbrack}\end{bmatrix} = {{{\begin{bmatrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} & {h_{1,3}\lbrack 1\rbrack} & {h_{1,4}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 1\rbrack} & {h_{2,2}\lbrack 1\rbrack} & {h_{2,3}\lbrack 1\rbrack} & {h_{2,4}\lbrack 1\rbrack}\end{bmatrix}\begin{bmatrix}x_{1} \\x_{2} \\x_{3} \\x_{4}\end{bmatrix}} + {\begin{bmatrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack}\end{bmatrix}\mspace{20mu}{{and}\;\begin{bmatrix}{y_{1}\lbrack 2\rbrack} \\{y_{2}\lbrack 2\rbrack}\end{bmatrix}}}} = {{\begin{bmatrix}{h_{1,1}\lbrack 2\rbrack} & {h_{1,2}\lbrack 2\rbrack} & {h_{1,3}\lbrack 2\rbrack} & {h_{1,4}\lbrack 2\rbrack} \\{h_{2,1}\lbrack 2\rbrack} & {h_{2,2}\lbrack 2\rbrack} & {h_{2,3}\lbrack 2\rbrack} & {h_{2,4}\lbrack 2\rbrack}\end{bmatrix}\begin{bmatrix}{- x_{2}^{*}} \\x_{1}^{*} \\{- x_{4}^{*}} \\x_{3}^{*}\end{bmatrix}} + {\begin{bmatrix}{z_{1}\lbrack 2\rbrack} \\{z_{2}\lbrack 2\rbrack}\end{bmatrix}\mspace{11mu}.}}}$The pre-processor for space-time code 310 may accordingly performAlamouti manipulation according to the equivalent model:

$\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 1\rbrack} \\{y_{1}^{*}\lbrack 2\rbrack} \\{y_{2}^{*}\lbrack 2\rbrack}\end{bmatrix} = {{\begin{bmatrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} & {h_{1,3}\lbrack 1\rbrack} & {h_{1,4}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 1\rbrack} & {h_{2,2}\lbrack 1\rbrack} & {h_{2,3}\lbrack 1\rbrack} & {h_{2,4}\lbrack 1\rbrack} \\{h_{1,2}^{*}\lbrack 2\rbrack} & {- \;{h_{1,1}^{*}\lbrack 2\rbrack}} & {h_{1,4}^{*}\lbrack 2\rbrack} & {- \;{h_{1,3}^{*}\lbrack 2\rbrack}} \\{h_{2,2}^{*}\lbrack 2\rbrack} & {- \;{h_{2,1}^{*}\lbrack 2\rbrack}} & {h_{2,4}^{*}\lbrack 2\rbrack} & {- \;{h_{2,3}^{*}\lbrack 2\rbrack}}\end{bmatrix}\begin{bmatrix}x_{1} \\x_{2} \\x_{3} \\x_{4}\end{bmatrix}} + {\begin{bmatrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack} \\{z_{1}^{*}\lbrack 2\rbrack} \\{z_{2}^{*}\lbrack 2\rbrack}\end{bmatrix}.}}$

It will be appreciated that Alamouti coding is discussed herein by wayof example only and that the smart receiver 300 may similarly processother forms of space-time encoding. In general, the pre-processor forspace-time code 310 may manipulate the received signals as necessary torepresent these received signals in terms of the original transmitsymbols. Thus, the smart receiver 300 may use the technique of modelingthe intended and interference signals, as well as generating andapplying an equivalence model as discussed above, to other types oflinearly processed signals.

As illustrated in FIG. 3, the demodulated signals generated by thedecoder 318 may be directed to a consuming component or application (notshown). With respect to the components 316 and 318, one of ordinaryskill in the art will appreciate that because the one or moretransmitters transmit data in particular timeslots according to aparticular transmission logic (e.g., transmitting the sequence s₁s₂simultaneously from two antennas), the order of the received symbolsmust be restored at the receiving end. Further, the decoder 318 may mapthe resulting symbols to the corresponding bits according to a schemewhich may be particular to the network or to the protocol that isutilized.

FIGS. 4-8 are flow diagrams of several example methods for performingMIMO decoding in the presence of various interfering sources. In someembodiments, each of the methods of FIGS. 4-8 may be the sole mode ofoperation of a corresponding smart receiver 300. In other embodiments, asmart receiver 300 may implement several or all of the methods of FIGS.4-8 and may include additional logic for selecting between the methodsin view of the MIMO mode of the intended streams (e.g., space-timeencoded, non-space-time encoded, etc.), the MIMO mode of the intendedstreams, computational capability (e.g., sufficient processing power toperform ML computation), equalizer preferences (e.g., ZF, MMSE, etc.),and other user- or network-configurable factors. Thus, each of themethods illustrated in FIGS. 4-8 may refer to separate embodiments or toa particular mode of a certain single embodiment. For ease ofexplanation and clarity, these diagrams do not include some of thecommon steps such as de-interleaving and decoding of the stream upon LLRcalculation.

Referring specifically to FIG. 4, an example method 400 for decodingnon-space-time-coded signals using equalization may begin in a block402, in which the smart receiver 300 constructs a communication systemand channel model as discussed above with reference to FIG. 3. Inparticular, the smart receiver 300 may obtain channel informationincluding modulation, gain, and MIMO mode parameters in a wirelessand/or wired manner to define a channel equivalent matrix, a noisecorrelation matrix, and the receive and transmit signal vectors. Next,in a block 404, the method 400 may equalize a subset of the streams tosimplify the subsequent calculation of the probable intended symbols.For example, using the zero-forcing technique, the smart receiver 300executing the method 400 may define an equivalent channel modelaccording to which an intended stream at a certain receive antenna canbe seen as unaffected by an intended stream transmitted to anotherreceive antenna. More generally, the method 400 may apply at this stageone or more of several equalization techniques such as those known inthe art, for example.

Finally, in a block 406, the smart receiver 300 may calculate the valueof each received symbol by applying a suitable statistical approach. Asdiscussed above, each signal from a transmit antenna may undergosignificant fading due to the distance of propagation, reflection offobstacles in the propagation path, interference due to othertransmitters, etc. and each of these factors may prevent the smartreceiver 300 from precisely knowing the value of each received symbol.However, by including the parameters related to the interfering channelsin the channel model, the smart receiver 300 may have a significantlybetter quality of information about the probable transmitted symbols.Accordingly, when the receiver 300 applies LLR or another statisticalmethodology to the received data in view of such factors as noisevariance, the dictionary of possible symbols, previously received data,etc., the probability of properly restoring the intended symbol issignificantly increased.

Referring to FIG. 5, an example method 420 for decodingnon-space-time-coded signals with no equalization is similar to themethod 400, except that the method 420 does not include channelequalizing. Instead, the method 420 decomposes the matrix correspondingto the channel which includes both the intended and interfering symbolsusing QR decomposition, for example. Alternatively, the method 420 mayskip the act of approximating the channel matrix and proceed directly toa block 426, in which the smart receiver 300 calculates LLR values usingthe ML approach. As indicated above, the ML approach may yield a moreaccurate value at the expense of higher computational complexity. It istherefore contemplated that in some embodiments, the method 400 may bepreferable to accelerate the decoding of the incoming data whereas inother embodiments, the smart receiver 300 may use a powerful processorto efficiently support ML computation.

With respect to FIG. 6, an example method 460 for decodingAlamouti-coded intended signals may similarly begin in a block 462 wherethe smart receiver may construct a model in view of the particularspace-time encoding technique. In the particular case illustrated inFIG. 6, the transmitters encode the intended signals according to theAlamouti formula. Thus, in a block 464, the smart receiver 300 mayperform the appropriate space-time receiver manipulation to prepare thereceived data for (optional) equalization in a block 466 anddemodulation in a block 468. In particular, the smart receiver 300 maytreat the Alamouti-coded intended signals as separate spatial streamswith pseudo-repetition.

In an example method 480 illustrated in FIG. 7, decoding may be appliedto Alamouti-coded interfering signals in a channel where the intendedsignals are not Alamouti-coded. The method 480 is similar to the method460. However, in blocks 482 and 484, the smart receiver 300 mayconstruct a transmission model and manipulate the model in view of thedifference in the encoding of the intended and interfering streams.

Finally, FIG. 8 illustrates an example method 500 for decoding signalswhen both the intended and the interfering signals are Alamouti-coded.The method 500 differs from the methods 460 and 480 primarily in theconstruction of the channel model and in receiver manipulation in blocks502 and 504, respectively.

Methods of decoding signals in the presence of interference sources suchas those described above may be utilized in various MIMO devices. Forexample, techniques such as described above may be utilized in basestations, access points, wireless routers, etc. Additionally, FIGS.9A-9F illustrate various devices in which signal decoding techniquessuch as described above, may be employed.

Referring now to FIG. 9A, such techniques may be utilized in a highdefinition television (HDTV) 1020. HDTV 1020 includes a mass datastorage 1027, an HDTV signal processing and control block 1022, a WLANinterface and memory 1028. HDTV 1020 receives HDTV input signals ineither a wired or wireless format and generates HDTV output signals fora display 1026. In some implementations, signal processing circuitand/or control circuit 1022 and/or other circuits (not shown) of HDTV1020 may process data, perform coding and/or encryption, performcalculations, format data and/or perform any other type of HDTVprocessing that may be required. The signal processing and/or controlcircuit 1022 may implement signal decoding techniques such as describedabove.

HDTV 1020 may communicate with a mass data storage 1027 that stores datain a nonvolatile manner such as optical and/or magnetic storage devices.The mass storage device may be a mini HDD that includes one or moreplatters having a diameter that is smaller than approximately 1.8″. HDTV1020 may be connected to memory 1028 such as RAM, ROM, low latencynonvolatile memory such as flash memory and/or other suitable electronicdata storage. HDTV 1020 also may support connections with a WLAN via aWLAN network interface 1029. The WLAN network interface 1029 mayimplement signal decoding techniques such as described above.

Referring now to FIG. 9B, such techniques may be utilized in a vehicle1030. The vehicle 1030 includes a control system that may include massdata storage 1046, as well as a WLAN interface 1048. The mass datastorage 1046 may support a powertrain control system 1032 that receivesinputs from one or more sensors 1036 such as temperature sensors,pressure sensors, rotational sensors, airflow sensors and/or any othersuitable sensors and/or that generates one or more output controlsignals 1038 such as engine operating parameters, transmission operatingparameters, and/or other control signals.

Control system 1040 may likewise receive signals from input sensors 1042and/or output control signals to one or more output devices 1044. Insome implementations, control system 1040 may be part of an anti-lockbraking system (ABS), a navigation system, a telematics system, avehicle telematics system, a lane departure system, an adaptive cruisecontrol system, a vehicle entertainment system such as a stereo, DVD,compact disc and the like.

Powertrain control system 1032 may communicate with mass data storage1027 that stores data in a nonvolatile manner such as optical and/ormagnetic storage devices. The mass storage device 1046 may be a mini HDDthat includes one or more platters having a diameter that is smallerthan approximately 1.8″. Powertrain control system 1032 may be connectedto memory 1047 such as RAM, ROM, low latency nonvolatile memory such asflash memory and/or other suitable electronic data storage. Powertraincontrol system 1032 also may support connections with a WLAN via a WLANnetwork interface 1048. The control system 1040 may also include massdata storage, memory and/or a WLAN interface (all not shown). In oneexemplary embodiment, the WLAN network interface 1048 may implementsignal decoding techniques such as described above.

Referring now to FIG. 9C, such techniques may be used in a cellularphone 1050 that may include a cellular antenna 1051. The cellular phone1050 may include either or both signal processing and/or controlcircuits, which are generally identified in FIG. 9C at 1052, a WLANnetwork interface 1068 and/or mass data storage 1064 of the cellularphone 1050. In some implementations, cellular phone 1050 includes amicrophone 1056, an audio output 1058 such as a speaker and/or audiooutput jack, a display 1060 and/or an input device 1062 such as akeypad, pointing device, voice actuation and/or other input device.Signal processing and/or control circuits 1052 and/or other circuits(not shown) in cellular phone 1050 may process data, perform codingand/or encryption, perform calculations, format data and/or performother cellular phone functions. The signal processing and/or controlcircuits 1052 may implement signal decoding techniques such as describedabove.

Cellular phone 1050 may communicate with mass data storage 1064 thatstores data in a nonvolatile manner such as optical and/or magneticstorage devices for example hard disk drives HDD and/or DVDs. The HDDmay be a mini HDD that includes one or more platters having a diameterthat is smaller than approximately 1.8″. Cellular phone 1050 may beconnected to memory 1066 such as RAM, ROM, low latency nonvolatilememory such as flash memory and/or other suitable electronic datastorage. Cellular phone 1050 also may support connections with a WLANvia a WLAN network interface 1068. The WLAN network interface 1068 mayimplement MCS selection techniques such as described above.

Referring now to FIG. 9D, such techniques may be utilized in a set topbox 1080. The set top box 1080 may include either or both signalprocessing and/or control circuits, which are generally identified inFIG. 9D at 1084, a WLAN interface and/or mass data storage 1090 of theset top box 1080. Set top box 1080 receives signals from a source suchas a broadband source and outputs standard and/or high definitionaudio/video signals suitable for a display 1088 such as a televisionand/or monitor and/or other video and/or audio output devices. Signalprocessing and/or control circuits 1084 and/or other circuits (notshown) of the set top box 1080 may process data, perform coding and/orencryption, perform calculations, format data and/or perfoim any otherset top box function. The signal processing and/or control circuits 1084may implement signal decoding techniques such as described above.

Set top box 1080 may communicate with mass data storage 1090 that storesdata in a nonvolatile manner and may use jitter measurement. Mass datastorage 1090 may include optical and/or magnetic storage devices forexample hard disk drives HDD and/or DVDs. The HDD may be a mini HDD thatincludes one or more platters having a diameter that is smaller thanapproximately 1.8″. Set top box 1080 may be connected to memory 1094such as RAM, ROM, low latency nonvolatile memory such as flash memoryand/or other suitable electronic data storage. Set top box 1080 also maysupport connections with a WLAN via a WLAN network interface 1096. TheWLAN network interface 1096 may implement MCS selection techniques suchas described above.

Referring now to FIG. 9E, such techniques may be used in a media player1100. The media player 1100 may include either or both signal processingand/or control circuits, which are generally identified in FIG. 9E at1104, a WLAN interface and/or mass data storage 1110 of the media player1100. In some implementations, media player 1100 includes a display 1107and/or a user input 1108 such as a keypad, touchpad and the like. Insome implementations, media player 1100 may employ a graphical userinterface (GUI) that typically employs menus, drop down menus, iconsand/or a point-and-click interface via display 1107 and/or user input1108. Media player 1100 further includes an audio output 1109 such as aspeaker and/or audio output jack. Signal processing and/or controlcircuits 1104 and/or other circuits (not shown) of media player 1100 mayprocess data, perform coding and/or encryption, perform calculations,format data and/or perform any other media player function.

Media player 1100 may communicate with mass data storage 1110 thatstores data such as compressed audio and/or video content in anonvolatile manner and may utilize jitter measurement. In someimplementations, the compressed audio files include files that arecompliant with MP3 format or other suitable compressed audio and/orvideo formats. The mass data storage may include optical and/or magneticstorage devices for example hard disk drives HDD and/or DVDs. The HDDmay be a mini HDD that includes one or more platters having a diameterthat is smaller than approximately 1.8″. Media player 1100 may beconnected to memory 1114 such as RAM, ROM, low latency nonvolatilememory such as flash memory and/or other suitable electronic datastorage. Media player 1100 also may support connections with a WLAN viaa WLAN network interface 1116. The WLAN network interface 1116 mayimplement signal decoding techniques such as described above.

Referring to FIG. 9F, such techniques may be utilized in a Voice overInternet Protocol (VoIP) phone 1150 that may include an antenna 1152.The VoIP phone 1150 may include either or both signal processing and/orcontrol circuits, which are generally identified in FIG. 9F at 1154, awireless interface and/or mass data storage of the VoIP phone 1150. Insome implementations, VoIP phone 1150 includes, in part, a microphone1158, an audio output 1160 such as a speaker and/or audio output jack, adisplay monitor 1162, an input device 1164 such as a keypad, pointingdevice, voice actuation and/or other input devices, and a WirelessFidelity (WiFi) communication module 1166. Signal processing and/orcontrol circuits 1154 and/or other circuits (not shown) in VoIP phone1150 may process data, perform coding and/or encryption, performcalculations, format data and/or perforin other VoIP phone functions.

VoIP phone 1150 may communicate with mass data storage 1156 that storesdata in a nonvolatile manner such as optical and/or magnetic storagedevices, for example hard disk drives HDD and/or DVDs. The HDD may be amini HDD that includes one or more platters having a diameter that issmaller than approximately 1.8″. VoIP phone 1150 may be connected tomemory 1157, which may be a RAM, ROM, low latency nonvolatile memorysuch as flash memory and/or other suitable electronic data storage. VoIPphone 1150 is configured to establish communications link with a VoIPnetwork (not shown) via WiFi communication module 1166. The WiFicommunication module 1166 may implement signal decoding techniques suchas described above.

At least some of the various blocks, operations, and techniquesdescribed above may be implemented in hardware, fir inware, software, orany combination of hardware, firmware, and/or software. When implementedin software or firmware, the software or firmware may be stored in anycomputer readable memory such as on a magnetic disk, an optical disk, orother storage medium, in a RAM or ROM or flash memory, processor, harddisk drive, optical disk drive, tape drive, etc. Likewise, the softwareor firmware may be delivered to a user or a system via any known ordesired delivery method including, for example, on a computer readabledisk or other transportable computer storage mechanism or viacommunication media. Communication media typically embodies computerreadable instructions, data structures, program modules or other data ina modulated data signal such as a carrier wave or other transportmechanism. The term “modulated data signal” means a signal that has oneor more of its characteristics set or changed in such a manner as toencode information in the signal. By way of example, and not limitation,communication media includes wired media such as a wired network ordirect-wired connection, and wireless media such as acoustic, radiofrequency, infrared and other wireless media. Thus, the software orfirmware may be delivered to a user or a system via a communicationchannel such as a telephone line, a DSL line, a cable television line, afiber optics line, a wireless communication channel, the Internet, etc.(which are viewed as being the same as or interchangeable with providingsuch software via a transportable storage medium). The software orfirmware may include machine readable instructions that are capable ofcausing one or more processors to perform various acts.

Although the forgoing text sets forth a detailed description of numerousdifferent embodiments, it should be understood that the scope of thepatent is defined by the words of the claims set forth at the end ofthis patent. The detailed description is to be construed as exemplaryonly and does not describe every possible embodiment because describingevery possible embodiment would be impractical, if not impossible.Numerous alternative embodiments could be implemented, using eithercurrent technology or technology developed after the filing date of thisdisclosure, which would still fall within the scope of the claims.

What is claimed is:
 1. A method of processing a signal transmitted via amultiple input multiple output (MIMO) communication channel, the methodcomprising: obtaining a first set of parameters associated with a firstplurality of transmitters transmitting a plurality of intended streams,wherein the first set of parameters includes modulation informationcorresponding to the plurality of intended streams; obtaining a secondset of parameters associated with an interference source, wherein thesecond set of parameters includes modulation information correspondingto the interference source; receiving a plurality of streams includingthe plurality of intended streams; pre-processing the plurality ofstreams to generate an equivalent receive signal model if one or more ofthe received plurality of streams are space-time-coded; demodulating theplurality of streams using the respective modulation informationcorresponding to the plurality of intended streams and to theinterference source, wherein the interference source includes aplurality of interfering streams; and decoding the plurality of intendedstreams.
 2. The method of claim 1, wherein receiving a plurality ofstreams includes receiving the plurality of streams at a plurality ofantennas; and wherein demodulating the plurality of streams furtherincludes using a plurality of noise parameters, wherein each of theplurality of noise parameters corresponds to a respective one of theplurality of antennas.
 3. The method of claim 1, wherein theinterference source includes a second plurality of transmitters; whereinthe first plurality of transmitters and the second plurality oftransmitters are associated with respective cells of a cellularcommunication network.
 4. The method of claim 3, wherein the cellularcommunication network is compliant with the Institute for Electrical andElectronics Engineers (IEEE) 802.16 Standard.
 5. The method of claim 1,wherein the first plurality of transmitters are antennas associated witha first base station, wherein the interference source includes aplurality of antennas associated with a second base station, wherein theintended streams are downlink streams from the first base station to amobile station; and wherein obtaining the second set of parametersassociated with the interference source includes processing channel dataassociated with the second base station.
 6. The method of claim 5,wherein processing the channel data associated with the second basestation includes processing a downlink map (DL-MAP) message.
 7. Themethod of claim 5, wherein processing the channel data associated withthe second base station includes processing a pseudo-noise (PN) sequencetransmitted at a pilot sub-carrier from the second base station.
 8. Themethod of claim 5, further comprising obtaining a third set ofparameters including processing channel data associated with a thirdbase station; and wherein demodulating the plurality of streams furtherincludes using the third set of parameters.
 9. The method of claim 1,wherein the first plurality of transmitters are associated with at leasta first mobile station, wherein the interference source is associatedwith at least a second mobile station, and wherein the intended streamsare uplink streams from the first mobile station to a first basestation; and wherein obtaining the second set of parameters associatedwith the interference source includes processing channel data associatedwith at least a second base station adjacent to the first base station.10. The method of claim 9, wherein obtaining the second set ofparameters includes receiving the second set of parameters via abackbone network to which the first base station and the second basestation are communicatively coupled.
 11. The method of claim 1, whereinobtaining the second set of parameters includes obtaining at least oneof a modulation scheme, channel gain information, or a MIMO modeassociated with the interference source.
 12. The method of claim 1,wherein demodulating the plurality of streams includes calculating alog-likelihood ratio (LLR) for each symbol in the plurality of intendedstreams according to a maximum-likelihood (ML) scheme.
 13. The method ofclaim 12, wherein calculating the log-likelihood ratio (LLR) includesperforming QR decomposition of a channel matrix corresponding to achannel including the plurality of intended streams and the interferingstreams.
 14. The method of claim 1, wherein processing the signalfurther includes equalizing a subset of streams within the plurality ofstreams prior to LLR calculation; and wherein demodulating the pluralityof streams includes calculating a log-likelihood ratio (LLR) for eachsymbol in the plurality of intended streams.
 15. The method of claim 1,wherein the plurality of intended streams are space-time-coded accordingto an Alamouti coding scheme.
 16. The method of claim 1, wherein theplurality of streams includes the plurality of interfering streams; andwherein processing the signal further includes: equalizing a subset ofthe plurality of streams; wherein none of the received plurality ofstreams is space-time-coded.
 17. The method of claim 16, whereinequalizing a subset of the plurality of streams includes applying atleast one of zero-forcing (ZF), minimum mean square error (MMSE), ZFdecision feedback equalization (DFE), or MMSE DFE techniques.
 18. Themethod of claim 1, wherein the plurality of streams includes theplurality of interfering streams; wherein none of the received pluralityof streams is space-time-coded; and wherein demodulating the pluralityof streams includes calculating LLR for each symbol in the plurality ofintended streams according to a maximum-likelihood (ML) scheme.
 19. Amethod of processing a signal transmitted via a multiple input multipleoutput (MIMO) communication channel, the method comprising: obtaining afirst set of parameters associated with a first plurality oftransmitters transmitting a plurality of intended streams; obtaining asecond set of parameters associated with an interference source;receiving a plurality of streams including the plurality of intendedstreams, wherein receiving a plurality of streams includes receivingeach of the plurality of streams at a respective one of a plurality ofreceive antennas; and demodulating the plurality of intended streamsusing the first set of parameters and the second set of parameters,wherein demodulating the plurality of intended streams includes applyinga model:y=Hx+z, ${y = {{\begin{bmatrix}y_{1} \\y_{2} \\\vdots \\y_{N_{R}}\end{bmatrix}\mspace{14mu} H} = {{\begin{bmatrix}h_{1,1} & h_{1,2} & \cdots & h_{1,N_{TS}} \\h_{2,1} & h_{2,2} & \cdots & h_{2,N_{TS}} \\\vdots & \vdots & \vdots & \vdots \\h_{N_{R},1} & h_{N_{R},2} & \cdots & h_{N_{R},N_{TS}}\end{bmatrix}\mspace{14mu} x} = \begin{bmatrix}x_{1} \\x_{2} \\\vdots \\x_{N_{TS}}\end{bmatrix}}}}\;$ ${z = \begin{bmatrix}z_{1} \\z_{2} \\\vdots \\z_{N_{R}}\end{bmatrix}};$ wherein N_(R) is a number of receive antennas; N_(TS)is a number of streams in the plurality of streams; y_(r) is a signalreceived at a receiver r, wherein each receiver r is included in theplurality of receivers; x_(s) is one of the plurality of intendedstreams for 1≦s≦N_(S) and one of a plurality of interfering streamsassociated with the interference source for N_(S+1)≦s≦N_(TS); andh_(r,s) is a channel gain associated with the stream x_(s) andcorresponding to the receiver r; and wherein at least one of i) theplurality of intended streams is Alamouti-coded, or ii) the plurality ofinterfering streams is Alamouti-coded.
 20. The method of claim 19,wherein the plurality of streams includes the plurality of interferingstreams associated with the interference source; and whereindemodulating the plurality of intended streams includes utilizing achannel equivalence model: ${\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 1\rbrack}\end{bmatrix} = {{{\begin{bmatrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} & {h_{1,3}\lbrack 1\rbrack} & {h_{1,4}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 1\rbrack} & {h_{2,2}\lbrack 1\rbrack} & {h_{2,3}\lbrack 1\rbrack} & {h_{2,4}\lbrack 1\rbrack}\end{bmatrix}\begin{bmatrix}x_{1} \\x_{2} \\{x_{3}\lbrack 1\rbrack} \\{x_{4}\lbrack 1\rbrack}\end{bmatrix}} + {\begin{bmatrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack}\end{bmatrix}\mspace{20mu}{{and}\;\begin{bmatrix}{y_{1}\lbrack 2\rbrack} \\{y_{2}\lbrack 2\rbrack}\end{bmatrix}}}} = {{\begin{bmatrix}{h_{1,1}\lbrack 2\rbrack} & {h_{1,2}\lbrack 2\rbrack} & {h_{1,3}\lbrack 2\rbrack} & {h_{1,4}\lbrack 2\rbrack} \\{h_{2,1}\lbrack 2\rbrack} & {h_{2,2}\lbrack 2\rbrack} & {h_{2,3}\lbrack 2\rbrack} & {h_{2,4}\lbrack 2\rbrack}\end{bmatrix}\begin{bmatrix}{- \; x_{2}^{*}} \\x_{1}^{*} \\{x_{3}\lbrack 2\rbrack} \\{x_{4}\lbrack 2\rbrack}\end{bmatrix}} + \begin{bmatrix}{z_{1}\lbrack 2\rbrack} \\{z_{2}\lbrack 2\rbrack}\end{bmatrix}}}}\;;$ wherein the plurality of intended streams isAlamouti-coded and the plurality of interfering streams is notAlamouti-coded.
 21. The method of claim 19, wherein the plurality ofstreams includes the plurality of interfering streams associated withthe interference source; and wherein demodulating the plurality ofintended streams includes utilizing a channel equivalence model:${\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 1\rbrack}\end{bmatrix} = {{{\begin{bmatrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} & {h_{1,3}\lbrack 1\rbrack} & {h_{1,4}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 1\rbrack} & {h_{2,2}\lbrack 1\rbrack} & {h_{2,3}\lbrack 1\rbrack} & {h_{2,4}\lbrack 1\rbrack}\end{bmatrix}\begin{bmatrix}{x_{1}\lbrack 1\rbrack} \\{x_{2}\lbrack 1\rbrack} \\x_{3} \\x_{4}\end{bmatrix}} + {\begin{bmatrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack}\end{bmatrix}\mspace{20mu}{{and}\;\begin{bmatrix}{y_{1}\lbrack 2\rbrack} \\{y_{2}\lbrack 2\rbrack}\end{bmatrix}}}} = {{\begin{bmatrix}{h_{1,1}\lbrack 2\rbrack} & {h_{1,2}\lbrack 2\rbrack} & {h_{1,3}\lbrack 2\rbrack} & {h_{1,4}\lbrack 2\rbrack} \\{h_{2,1}\lbrack 2\rbrack} & {h_{2,2}\lbrack 2\rbrack} & {h_{2,3}\lbrack 2\rbrack} & {h_{2,4}\lbrack 2\rbrack}\end{bmatrix}\begin{bmatrix}{x_{1}\lbrack 2\rbrack} \\{x_{2}\lbrack 2\rbrack} \\{- x_{4}^{*}} \\{- x_{3}^{*}}\end{bmatrix}} + \begin{bmatrix}{z_{1}\lbrack 2\rbrack} \\{z_{2}\lbrack 2\rbrack}\end{bmatrix}}}}\mspace{11mu}$ wherein the plurality of intended streamsis not Alamouti-coded and the plurality of interfering streams isAlamouti-coded.
 22. The method of claim 19, wherein the plurality ofstreams includes the plurality of interfering streams associated withthe interference source; and wherein demodulating the plurality ofintended streams includes utilizing a channel equivalence model:$\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 1\rbrack} \\{y_{1}^{*}\lbrack 2\rbrack} \\{y_{2}^{*}\lbrack 2\rbrack}\end{bmatrix} = {{\begin{bmatrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} & {h_{1,3}\lbrack 1\rbrack} & {h_{1,4}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 1\rbrack} & {h_{2,2}\lbrack 1\rbrack} & {h_{2,3}\lbrack 1\rbrack} & {h_{2,4}\lbrack 1\rbrack} \\{h_{1,2}^{*}\lbrack 2\rbrack} & {- \;{h_{1,1}^{*}\lbrack 2\rbrack}} & {h_{1,4}^{*}\lbrack 2\rbrack} & {- \;{h_{1,3}^{*}\lbrack 2\rbrack}} \\{h_{2,2}^{*}\lbrack 2\rbrack} & {- \;{h_{2,1}^{*}\lbrack 2\rbrack}} & {h_{2,4}^{*}\lbrack 2\rbrack} & {- \;{h_{2,3}^{*}\lbrack 2\rbrack}}\end{bmatrix}\begin{bmatrix}x_{1} \\x_{2} \\x_{3} \\x_{4}\end{bmatrix}} + {\begin{bmatrix}\begin{matrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack}\end{matrix} \\{z_{1}^{*}\lbrack 2\rbrack} \\{z_{2}^{*}\lbrack 2\rbrack}\end{bmatrix}.}}$ wherein the plurality of intended streams isAlamouti-coded and the plurality of interfering streams isAlamouti-coded.
 23. A smart receiver for processing a signal transmittedvia a multiple input multiple output (MIMO) communication channel,comprising: a plurality of antennas which receive a plurality of streamsincluding a set of intended streams and a set of interference streamsvia the MIMO channel; a demodulator that demodulates the plurality ofstreams using at least first channel data associated with the set ofintended streams and second channel data associated with the set ofinterference streams, wherein the demodulator demodulates the pluralityof streams at least in part by applying a model:y=Hx+z, ${y = {{\begin{bmatrix}y_{1} \\y_{2} \\\vdots \\y_{N_{R}}\end{bmatrix}\mspace{14mu} H} = {{\begin{bmatrix}h_{1,1} & h_{1,2} & \cdots & h_{1,N_{TS}} \\h_{2,1} & h_{2,2} & \cdots & h_{2,N_{TS}} \\\vdots & \vdots & \vdots & \vdots \\h_{N_{R},1} & h_{N_{R},2} & \cdots & h_{N_{R},N_{TS}}\end{bmatrix}\mspace{14mu} x} = \begin{bmatrix}x_{1} \\x_{2} \\\vdots \\x_{N_{TS}}\end{bmatrix}}}}\;$ ${z = \begin{bmatrix}z_{1} \\z_{2} \\\vdots \\z_{N_{R}}\end{bmatrix}};$ wherein N_(R) is a number of receive antennas; N_(TS)is a number of streams in the plurality of streams; y_(r) is a signalreceived at a receiver r, wherein each receiver r is included in theplurality of receivers; x_(s) is one stream of the set of intendedstreams for 1≦s≦N_(S) and one stream of the set of interference streamsfor N_(S+1)≦s≦N_(TS); and h_(r,s) is a channel gain associated with thestream x_(s) and corresponding to the receiver r; and wherein at leastone of i) the set of intended streams is Alamouti-coded, or the set ofinterfering streams is Alamouti-coded; a deinterleaver that receives thedemodulated plurality of streams and restores a sequence of symbols; anda decoder that decodes the restored sequence of symbols.
 24. The smartreceiver of claim 23, further comprising a pre-processor that processesspace-time encoding of at least a subset of the plurality of streams.25. The smart receiver of claim 24, wherein the pre-processor processesAlamouti-encoded signals.
 26. The smart receiver of claim 23, furthercomprising an equalizer that equalizes a subset of the plurality ofstreams.
 27. A base station incorporating the smart receiver of claim23, wherein the smart receiver further comprises a wired networkconnection to obtain channel data from at least one other base station.28. A method of processing, at a first wireless device, a signalincluding a plurality of streams from a second wireless devicecommunicating in a MIMO mode with the first wireless device, the methodcomprising: receiving a first channel description associated with afirst cell in which the first wireless device and the second wirelessdevice operate, wherein receiving the first channel description includesreceiving modulation information corresponding to the first cell;receiving a second channel description associated with a second cell,wherein receiving the second channel description includes receivingmodulation information corresponding to the second cell; receiving thesignal, wherein the signal includes i) a plurality of intended streamstransmitted from the second wireless device via a plurality oftransmitters and ii) a plurality of interference streams; pre-processingthe signal to generate an equivalent receive signal model if one or moreof the received plurality of streams are space-time-coded; demodulatingthe signal using the modulation information corresponding to the firstcell and the modulation information corresponding to the second cell;determining LLR values using the equivalent receive signal model; anddecoding the signal using the determined LLR values.
 29. The method ofclaim 28, wherein the first wireless device is one of a mobile stationor a base station and wherein the second wireless device is the otherone of the mobile station or the base station.
 30. The method of claim28, wherein receiving the first channel description includes receiving afirst downlink map (DL-MAP) message specifying resource allocation inthe first cell associated with a network compliant with the Institutefor Electrical and Electronics Engineers (IEEE) 802.16 Standard, andwherein receiving the second channel description includes receiving asecond DL-MAP message specifying resource allocation in the second cellassociated with the network.
 31. The method of claim 28, whereingenerating the equivalent receive signal model includes estimatingchannel gain associated with each of the plurality of intended streamsand each of the plurality of interference streams.
 32. The method ofclaim 28, wherein generating the equivalent receive signal modelincludes obtaining at least one of a MIMO mode, channel gaininformation, and modulation information associated with the second cell.33. The smart receiver of claim 23, wherein the demodulator demodulatesthe plurality of streams at least in part by utilizing a channelequivalence model: ${\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 1\rbrack}\end{bmatrix} = {{{\begin{bmatrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} & {h_{1,3}\lbrack 1\rbrack} & {h_{1,4}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 1\rbrack} & {h_{2,2}\lbrack 1\rbrack} & {h_{2,3}\lbrack 1\rbrack} & {h_{2,4}\lbrack 1\rbrack}\end{bmatrix}\begin{bmatrix}x_{1} \\x_{2} \\{x_{3}\lbrack 1\rbrack} \\{x_{4}\lbrack 1\rbrack}\end{bmatrix}} + {\begin{bmatrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack}\end{bmatrix}\mspace{20mu}{{and}\;\begin{bmatrix}{y_{1}\lbrack 2\rbrack} \\{y_{2}\lbrack 2\rbrack}\end{bmatrix}}}} = {{\begin{bmatrix}{h_{1,1}\lbrack 2\rbrack} & {h_{1,2}\lbrack 2\rbrack} & {h_{1,3}\lbrack 2\rbrack} & {h_{1,4}\lbrack 2\rbrack} \\{h_{2,1}\lbrack 2\rbrack} & {h_{2,2}\lbrack 2\rbrack} & {h_{2,3}\lbrack 2\rbrack} & {h_{2,4}\lbrack 2\rbrack}\end{bmatrix}\begin{bmatrix}{- x_{2}^{*}} \\x_{1}^{*} \\{x_{3}\lbrack 2\rbrack} \\{x_{4}\lbrack 2\rbrack}\end{bmatrix}} + \begin{bmatrix}{z_{1}\lbrack 2\rbrack} \\{z_{2}\lbrack 2\rbrack}\end{bmatrix}}}}\mspace{11mu};$ wherein the set of intended streams isAlamouti-coded and the set of interfering streams is not Alamouti-coded.34. The smart receiver of claim 23, wherein the demodulator demodulatesthe plurality of streams at least in part by utilizing a channelequivalence model: ${\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 1\rbrack}\end{bmatrix} = {{{\begin{bmatrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} & {h_{1,3}\lbrack 1\rbrack} & {h_{1,4}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 1\rbrack} & {h_{2,2}\lbrack 1\rbrack} & {h_{2,3}\lbrack 1\rbrack} & {h_{2,4}\lbrack 1\rbrack}\end{bmatrix}\begin{bmatrix}{x_{1}\lbrack 1\rbrack} \\{x_{2}\lbrack 1\rbrack} \\x_{3} \\x_{4}\end{bmatrix}} + {\begin{bmatrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack}\end{bmatrix}\mspace{20mu}{{and}\;\begin{bmatrix}{y_{1}\lbrack 2\rbrack} \\{y_{2}\lbrack 2\rbrack}\end{bmatrix}}}} = {{\begin{bmatrix}{h_{1,1}\lbrack 2\rbrack} & {h_{1,2}\lbrack 2\rbrack} & {h_{1,3}\lbrack 2\rbrack} & {h_{1,4}\lbrack 2\rbrack} \\{h_{2,1}\lbrack 2\rbrack} & {h_{2,2}\lbrack 2\rbrack} & {h_{2,3}\lbrack 2\rbrack} & {h_{2,4}\lbrack 2\rbrack}\end{bmatrix}\begin{bmatrix}{x_{1}\lbrack 2\rbrack} \\{x_{2}\lbrack 2\rbrack} \\{- x_{4}^{*}} \\{- x_{3}^{*}}\end{bmatrix}} + \begin{bmatrix}{z_{1}\lbrack 2\rbrack} \\{z_{2}\lbrack 2\rbrack}\end{bmatrix}}}}\mspace{11mu}$ wherein the set of intended streams isnot Alamouti-coded and the set of interfering streams is Alamouti-coded.35. The smart receiver of claim 23, wherein the demodulator demodulatesthe plurality of streams at least in part by utilizing a channelequivalence model: $\begin{bmatrix}{y_{1}\lbrack 1\rbrack} \\{y_{2}\lbrack 1\rbrack} \\{y_{1}^{*}\lbrack 2\rbrack} \\{y_{2}^{*}\lbrack 2\rbrack}\end{bmatrix} = {{\begin{bmatrix}{h_{1,1}\lbrack 1\rbrack} & {h_{1,2}\lbrack 1\rbrack} & {h_{1,3}\lbrack 1\rbrack} & {h_{1,4}\lbrack 1\rbrack} \\{h_{2,1}\lbrack 1\rbrack} & {h_{2,2}\lbrack 1\rbrack} & {h_{2,3}\lbrack 1\rbrack} & {h_{2,4}\lbrack 1\rbrack} \\{h_{1,2}^{*}\lbrack 2\rbrack} & {- \;{h_{1,1}^{*}\lbrack 2\rbrack}} & {h_{1,4}^{*}\lbrack 2\rbrack} & {- \;{h_{1,3}^{*}\lbrack 2\rbrack}} \\{h_{2,2}^{*}\lbrack 2\rbrack} & {- \;{h_{2,1}^{*}\lbrack 2\rbrack}} & {h_{2,4}^{*}\lbrack 2\rbrack} & {- \;{h_{2,3}^{*}\lbrack 2\rbrack}}\end{bmatrix}\begin{bmatrix}x_{1} \\x_{2} \\x_{3} \\x_{4}\end{bmatrix}} + \begin{bmatrix}\begin{matrix}{z_{1}\lbrack 1\rbrack} \\{z_{2}\lbrack 1\rbrack}\end{matrix} \\{z_{1}^{*}\lbrack 2\rbrack} \\{z_{2}^{*}\lbrack 2\rbrack}\end{bmatrix}}$ wherein the set of intended streams is Alamouti-codedand the set of interfering streams is Alamouti-coded.